The candidate, Dr. Arthur Mayeno, is applying for a K25 Mentored Quantitative Research Career Development Award, in hope of achieving his long-term goal of becoming an independent researcher in quantitative and computational modeling of biological systems. After earning a Ph.D. in organic chemistry and working in the pharmaceutical industry for several years as an analytical chemist, he wishes to transition back into academic research and apply his knowledge and experience in chemistry toward biomedical research. Professor Raymond Yang, in the Department of Environmental and Radiological Health Sciences at Colorado State University, has agreed to be his mentor. Both he and the Department are committed to helping Dr. Mayeno achieve his goals by providing guidance, support, and the research environment. Dr. Mayeno has proposed a career development plan tailored to his needs that include coursework, participation at meetings and workshops, training in the responsible conduct of research, limited teaching, and research in a relevant area of computational toxicology. The proposed research centers on modeling the biotransformation of polychlorinated biphenyls (PCBs), a family of 209 related chemicals, which are ubiquitous environmental pollutants. Although it is known that PCBs and their metabolites exert biological and toxic effects on humans and other organisms, the underlying mechanism behind these health effects remains unclear due, in part, to the complexity of the biochemical interactions involved. A successful model should permit the study and simulation of the metabolism of complex PCB mixtures more representative of the true exposure, and more importantly, provide insight into the underlying molecular basis for the toxicology of PCBs. The proposal herein represents just the first step in developing a comprehensive model and will focus on modeling the biotransformation of PCBs by a single relevant cytochrome P450 (CYP) isozyme, CYP1A1. The research will be accomplished via the following specific aims: In specific aim 1, quantitative structure-reactivity correlations (QSRCs) will be determined that correlate the molecular parameters of a PCB with its rate of metabolism and the site(s) of reaction within the PCB molecule. In addition, a database of "reaction rules" describing the reactions catalyzed by CYP1A1 will be developed to represent the biotransformation pathways. In specific aim 2, the QSRCs and reaction rules will be used to create reaction network models for PCB metabolism. Finally, in specific aim 3, the model(s) will be refined and validated.